Python API reference¶

The Python API is synchronous and currently marked beta. Prefer explicit keyword arguments and inspect nonzero results.

`BatchEvent`¶

One privacy-redacted JSON Lines event emitted by a batch run.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`BatchItemOutcome`¶

Stable per-item result, including resumed and cancelled jobs.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`BatchJob`¶

One stable job identity paired with an immutable typed plan.

`BatchManifest`¶

Strict versioned profile-job manifest compiled through the typed planner.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`BatchPolicy`¶

Explicit concurrency, retry, input-size, and timeout limits.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`BatchRun`¶

Versioned ordered outcome for one bounded batch execution.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`BatchRunner`¶

Execute validated jobs concurrently with receipts, events, retry, and resume.

`run(self, jobs: 'Iterable[BatchJob]', *, policy: 'BatchPolicy | None' = None, cancellation: 'threading.Event | None' = None, event_callback: 'Callable[[BatchEvent], None] | None' = None, state_path: 'str | Path | None' = None, resume: 'bool' = False, receipt_dir: 'str | Path | None' = None, hash_content: 'bool' = False) -> 'BatchRun'`¶

Run jobs once, retry transient failures, and persist successful signatures atomically.

`CapabilityUnavailableError`¶

The installed FFmpeg build cannot satisfy the requested workflow.

`CapabilityInventory`¶

Versioned inventory of an installed FFmpeg executable.

`missing(self, requirements: 'tuple[str, ...]') -> 'tuple[str, ...]'`¶

No public docstring is available.

`supports(self, requirement: 'str') -> 'bool'`¶

Check a normalized kind:name requirement.

`to_dict(self) -> 'dict[str, Any]'`¶

No public docstring is available.

`CapturePolicy`¶

Python 3.10-compatible string enumeration.

`CompressOptions`¶

CompressOptions(target_size_bytes: 'int | None' = None, crf: 'int' = 23, two_pass: 'bool' = True, video_codec: 'str' = 'libx264', audio_codec: 'str' = 'aac', video_bitrate: 'str | None' = None, audio_bitrate: 'str' = '128k', preset: 'str' = 'medium', pixel_format: 'str' = 'yuv420p', threads: 'int | None' = None, container_overhead_percent: 'float' = 5.0, minimum_video_bitrate: 'int' = 102400)

`ConvertOptions`¶

ConvertOptions(video_codec: 'str | None' = None, audio_codec: 'str | None' = None, video_bitrate: 'str | None' = None, audio_bitrate: 'str | None' = None, pixel_format: 'str' = 'yuv420p', threads: 'int | None' = None, audio_only: 'bool' = False, hardware_acceleration: 'str | None' = None, preserve_all_streams: 'bool' = False)

`EnvironmentUnavailableError`¶

A required executable or host resource is unavailable.

`ExecutionPlan`¶

Deterministic, non-shell execution plan for one media workflow.

`to_dict(self) -> 'dict[str, Any]'`¶

No public docstring is available.

`ExecutionPolicy`¶

Explicit process, overwrite, capture, and cleanup behavior.

`ExecutionStep`¶

One named argument-vector step inside a multi-pass plan.

`FFmpegRunner`¶

Execute typed workflows or an explicit non-shell argument vector.

`adjust_speed(self, input_file: 'str', output_file: 'str', speed_factor: 'float' = 1.0, audio_pitch: 'bool' = True, *, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

Plan, preflight, and execute typed video speed adjustment.

compress(self, input_file: 'str', output_file: 'str', *, target_size_kb: 'int | None' = None, crf: 'int' = 23, two_pass: 'bool' = True, video_codec: 'str' = 'libx264', audio_codec: 'str' = 'aac', video_bitrate: 'str | None' = None, audio_bitrate: 'str' = '128k', preset: 'str' = 'medium', pixel_format: 'str' = 'yuv420p', threads: 'int | None' = None, container_overhead_percent: 'float' = 5.0, minimum_video_bitrate: 'int' = 102400, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'¶

Plan, preflight, and execute typed single- or two-pass compression.

`convert(self, input_file: 'str', output_file: 'str', *, video_codec: 'str | None' = None, audio_codec: 'str | None' = None, video_bitrate: 'str | None' = None, audio_bitrate: 'str | None' = None, pixel_format: 'str' = 'yuv420p', threads: 'int | None' = None, audio_only: 'bool' = False, hardware_acceleration: 'str | None' = None, preserve_all_streams: 'bool' = False, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

Plan, preflight, and execute a typed conversion.

`execute_plan(self, plan: 'ExecutionPlan', *, cancellation: 'threading.Event | None' = None, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

Execute a typed plan and return a stable structured result.

`extract_audio(self, input_file: 'str', output_file: 'str', *, audio_codec: 'str | None' = None, audio_bitrate: 'str' = '192k', sample_rate: 'int | None' = None, channels: 'int | None' = None, threads: 'int | None' = None, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

Plan, preflight, and execute typed audio extraction.

`extract_thumbnail(self, input_file: 'str', output_file: 'str', timestamp: 'str' = '00:00:01', width: 'int' = 320, height: 'int | None' = None, quality: 'int' = 2, *, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

Plan, preflight, and execute typed thumbnail extraction.

`generate_waveform(self, input_file: 'str', output_file: 'str', width: 'int' = 800, height: 'int' = 200, colors: 'str' = 'white', *, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

Plan, preflight, and execute typed waveform rendering.

`get_version(self) -> 'str'`¶

Return the FFmpeg version banner line.

`resize(self, input_file: 'str', output_file: 'str', width: 'int', height: 'int', *, video_codec: 'str | None' = None, audio_codec: 'str | None' = None, pixel_format: 'str' = 'yuv420p', threads: 'int | None' = None, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

Plan, preflight, and execute a typed resize.

`run(self, args: 'list[str]', progress_callback: 'Callable[[dict[str, object]], None] | None' = None, *, overwrite: 'OverwritePolicy' = <OverwritePolicy.REFUSE: 'refuse'>) -> 'subprocess.CompletedProcess[str]'`¶

Run a raw argument vector without a shell and with explicit overwrite policy.

`run_with_progress(self, args: 'list[str]', show_percentage: 'bool' = True, *, overwrite: 'OverwritePolicy' = <OverwritePolicy.REFUSE: 'refuse'>) -> 'subprocess.CompletedProcess[str]'`¶

Run the low-level escape hatch and print its legacy progress stream.

`FFprobeRunner`¶

A runner for extracting metadata from media files using FFprobe.

`get_bitrate(self, input_file: 'str') -> 'int | None'`¶

Get the bitrate of a media file.

Args: input_file: Path to the media file

Returns: Bitrate in bits per second

`get_duration(self, input_file: 'str') -> 'float'`¶

Get the duration of a media file in seconds.

Args: input_file: Path to the media file

Returns: Duration in seconds

`get_resolution(self, input_file: 'str') -> 'tuple | None'`¶

Get the resolution of a video file.

Args: input_file: Path to the video file

Returns: Tuple of (width, height) or None if not a video

`get_version(self) -> 'str'`¶

Get the FFprobe version.

Returns: Version string

`probe(self, input_file: 'str', *, raw: 'bool' = False) -> 'dict[str, Any]'`¶

Extract simplified metadata from a media file.

Args: input_file: Path to the media file

Returns: Simplified metadata dictionary derived from FFprobe JSON

`probe_media(self, input_file: 'str') -> 'MediaInfo'`¶

Return typed metadata while retaining decision-relevant stream details.

`probe_raw(self, input_file: 'str') -> 'dict[str, Any]'`¶

Return the complete FFprobe JSON document without dropping fields.

`JobCancelledError`¶

A caller explicitly cancelled a running job.

`JobExecutionError`¶

FFmpeg or FFprobe started but the media job failed.

`JobResult`¶

Stable execution result with diagnostics and output evidence.

`to_dict(self) -> 'dict[str, Any]'`¶

No public docstring is available.

`JobStatus`¶

Python 3.10-compatible string enumeration.

`JobTimeoutError`¶

A job exceeded its explicit timeout.

`MediaInfo`¶

Typed container, stream, and chapter information from FFprobe.

`to_dict(self) -> 'dict[str, Any]'`¶

No public docstring is available.

`OverwritePolicy`¶

Python 3.10-compatible string enumeration.

`PipelineCachePolicy`¶

Optional output-validity cache; content hashing is explicit.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`PipelineCompiler`¶

Resolve variables/dependencies and compile every step through the typed planner.

`compile(self, spec: 'PipelineSpec', *, variables: 'dict[str, str] | None' = None, force: 'bool' = False, timeout_seconds: 'float | None' = None, cache_enabled: 'bool | None' = None) -> 'PipelinePlan'`¶

No public docstring is available.

`PipelineEvent`¶

PipelineEvent(sequence: 'int', event: 'str', step_id: 'str', detail: 'str | None' = None, schema_version: 'str' = '1.0')

`to_dict(self, secrets: 'tuple[str, ...]' = ()) -> 'dict[str, object]'`¶

No public docstring is available.

`PipelinePlan`¶

Compiled DAG whose steps contain argument arrays, never shell strings.

`graph(self, format: 'str' = 'text') -> 'str'`¶

Render the dependency DAG as text, Mermaid, or Graphviz DOT.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`PipelinePreflightEngine`¶

Preflight an entire DAG while explicitly deferring dependency outputs.

`prepare(self, pipeline: 'PipelinePlan', *, allow_existing_outputs: 'bool' = False) -> 'PreparedPipeline'`¶

No public docstring is available.

`PipelineRun`¶

PipelineRun(pipeline: 'PipelinePlan', items: 'tuple[PipelineStepOutcome, ...]', schema_version: 'str' = '1.0')

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`PipelineRunner`¶

Execute a prepared DAG with dependency blocking, cancellation, resume, and caching.

`run(self, pipeline: 'PipelinePlan', *, cancellation: 'threading.Event | None' = None, state_path: 'str | Path | None' = None, resume: 'bool' = False, receipt_dir: 'str | Path | None' = None, hash_content: 'bool' = False, event_callback: 'Any' = None) -> 'PipelineRun'`¶

No public docstring is available.

`PipelineSpec`¶

Versioned pipeline source with strict variables, cache, and typed steps.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`PipelineStepOutcome`¶

PipelineStepOutcome(step_id: 'str', status: 'str', cache_key: 'str', execution: 'WorkflowExecution | None' = None, receipt: 'str | None' = None, detail: 'str | None' = None)

`to_dict(self, secrets: 'tuple[str, ...]' = ()) -> 'dict[str, object]'`¶

No public docstring is available.

`PipelineStepPlan`¶

One topologically ordered typed plan and its dependencies.

`PipelineStepSpec`¶

One strict declarative step before variable and dependency resolution.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`Profile`¶

A named, versioned set of choices for one supported workflow.

`to_dict(self) -> 'dict[str, Any]'`¶

No public docstring is available.

`ProfileRegistry`¶

Resolve built-in profiles and strictly validate local profile files.

`get(self, name: 'str') -> 'Profile'`¶

No public docstring is available.

`list(self) -> 'tuple[Profile, ...]'`¶

No public docstring is available.

`load_file(self, path: 'str | Path') -> 'Profile'`¶

Load one strict versioned profile from JSON or TOML.

`plan(self, name: 'str', planner: 'WorkflowPlanner', input_file: 'str', output_file: 'str', *, subtitle_file: 'str | None' = None, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

Compile a maintained built-in profile through the shared typed planner.

`PreparedPipeline`¶

Whole-pipeline structural, capability, and external-input preflight facts.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`PreparedWorkflow`¶

An immutable plan paired with its non-mutating preflight facts.

`PreflightCheck`¶

One deterministic preflight fact.

`PreflightEngine`¶

Check a plan without creating directories, outputs, or temporary files.

`check(self, plan: 'ExecutionPlan') -> 'PreflightReport'`¶

No public docstring is available.

`PreflightReport`¶

Versioned preflight result shared by human and JSON presenters.

`render(self) -> 'str'`¶

No public docstring is available.

`to_dict(self) -> 'dict[str, Any]'`¶

No public docstring is available.

`ProgressCallback`¶

A helper class for creating progress callbacks with context.

`ProgressEvent`¶

Versioned progress fact suitable for callbacks or JSON Lines output.

`to_dict(self) -> 'dict[str, Any]'`¶

No public docstring is available.

`ProgressTracker`¶

Tracks FFmpeg progress by parsing progress output.

`run(self, cmd: list) -> subprocess.CompletedProcess`¶

Run a command and track progress.

Args: cmd: Command to run

Returns: CompletedProcess instance

`simple_progress_callback(progress: dict[str, typing.Any])`¶

A simple progress callback that prints progress to console.

Args: progress: Progress dictionary

`PyFFmpegCoreError`¶

Base error carrying a stable machine-readable category.

`ReceiptBuilder`¶

Build redacted receipts from the same prepared workflow and stable results.

`build(self, batch: 'WorkflowBatch', *, hash_content: 'bool' = False) -> 'RunReceipt'`¶

Create a private-by-default receipt; content hashes are explicit opt-in.

`ResizeOptions`¶

ResizeOptions(width: 'int', height: 'int', video_codec: 'str | None' = None, audio_codec: 'str | None' = None, pixel_format: 'str' = 'yuv420p', threads: 'int | None' = None)

`RunReceipt`¶

Validated schema 1.0 receipt suitable for storage or bug reports.

`to_dict(self) -> 'dict[str, Any]'`¶

No public docstring is available.

`to_json(self) -> 'str'`¶

No public docstring is available.

`write(self, path: 'str | Path') -> 'Path'`¶

No public docstring is available.

`StreamInfo`¶

Typed stream facts while preserving metadata needed for safe decisions.

`TemporaryFilePolicy`¶

Python 3.10-compatible string enumeration.

`ValidationError`¶

User input or policy is invalid before execution starts.

`WorkflowPlanner`¶

Build deterministic plans used by CLI, Python, examples, and pipelines.

`compress(self, input_file: 'str', output_file: 'str', options: 'CompressOptions | None' = None, *, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`concat(self, input_files: 'list[str]', output_file: 'str', *, mode: 'str' = 'copy', video_codec: 'str' = 'libx264', audio_codec: 'str' = 'aac', force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`convert(self, input_file: 'str', output_file: 'str', options: 'ConvertOptions | None' = None, *, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`extract_audio(self, input_file: 'str', output_file: 'str', *, audio_codec: 'str | None' = None, audio_bitrate: 'str' = '192k', sample_rate: 'int | None' = None, channels: 'int | None' = None, threads: 'int | None' = None, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`image(self, input_file: 'str', output_file: 'str', *, quality: 'int' = 85, resize: 'tuple[int, int] | None' = None, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

Plan one still-image conversion without routing through a directory batch.

`images(self, action: 'str', input_dir: 'str', output_dir: 'str', *, output_format: 'str' = 'jpg', quality: 'int' = 85, resize: 'tuple[int, int] | None' = None, max_width: 'int' = 1920, max_height: 'int' = 1080, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`mix_audio(self, action: 'str', input_files: 'list[str]', output_file: 'str', *, volumes: 'list[float] | None' = None, crossfade_duration: 'float' = 2.0, background_volume: 'float' = 0.3, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`normalize_audio(self, input_file: 'str', output_file: 'str', *, method: 'str' = 'loudnorm', target_i: 'float' = -16.0, target_tp: 'float' = -1.5, target_lra: 'float' = 11.0, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`resize(self, input_file: 'str', output_file: 'str', options: 'ResizeOptions', *, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`speed(self, kind: 'str', input_file: 'str', output_file: 'str', *, factor: 'float', preserve_pitch: 'bool' = True, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`subtitles(self, action: 'str', video_file: 'str', output_file: 'str', *, subtitle_file: 'str | None' = None, language: 'str' = 'eng', stream_index: 'int' = 0, font_size: 'int' = 24, font_color: 'str' = '&HFFFFFF', force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`thumbnail(self, input_file: 'str', output_file: 'str', *, timestamp: 'str' = '00:00:01', width: 'int' = 320, height: 'int | None' = None, quality: 'int' = 2, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`waveform(self, input_file: 'str', output_file: 'str', *, width: 'int' = 800, height: 'int' = 200, colors: 'str' = 'white', force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

No public docstring is available.

`WorkflowBatch`¶

Versioned machine-readable outcome for a single or multi-item plan.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

`WorkflowEngine`¶

Compile, preflight, and execute every supported workflow through one public layer.

`prepare(self, plan: 'ExecutionPlan') -> 'PreparedWorkflow'`¶

Preflight an already compiled plan without mutating media or output paths.

`run(self, plan: 'ExecutionPlan | PreparedWorkflow', *, cancellation: 'threading.Event | None' = None, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'WorkflowBatch'`¶

Execute a single workflow or an item-aware image batch with stable results.

`WorkflowExecution`¶

Preflight and execution facts for one input/output item.

`to_dict(self) -> 'dict[str, object]'`¶

No public docstring is available.

Python API reference¶

BatchEvent¶

to_dict(self) -> 'dict[str, object]'¶

BatchItemOutcome¶

to_dict(self) -> 'dict[str, object]'¶

BatchJob¶

BatchManifest¶

to_dict(self) -> 'dict[str, object]'¶

BatchPolicy¶

to_dict(self) -> 'dict[str, object]'¶

BatchRun¶

to_dict(self) -> 'dict[str, object]'¶

BatchRunner¶

CapabilityUnavailableError¶

CapabilityInventory¶

missing(self, requirements: 'tuple[str, ...]') -> 'tuple[str, ...]'¶

supports(self, requirement: 'str') -> 'bool'¶

to_dict(self) -> 'dict[str, Any]'¶

CapturePolicy¶

CompressOptions¶

ConvertOptions¶

EnvironmentUnavailableError¶

ExecutionPlan¶

to_dict(self) -> 'dict[str, Any]'¶

ExecutionPolicy¶

ExecutionStep¶

FFmpegRunner¶

adjust_speed(self, input_file: 'str', output_file: 'str', speed_factor: 'float' = 1.0, audio_pitch: 'bool' = True, *, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'¶

execute_plan(self, plan: 'ExecutionPlan', *, cancellation: 'threading.Event | None' = None, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'¶

extract_thumbnail(self, input_file: 'str', output_file: 'str', timestamp: 'str' = '00:00:01', width: 'int' = 320, height: 'int | None' = None, quality: 'int' = 2, *, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'¶

generate_waveform(self, input_file: 'str', output_file: 'str', width: 'int' = 800, height: 'int' = 200, colors: 'str' = 'white', *, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'¶

get_version(self) -> 'str'¶

run(self, args: 'list[str]', progress_callback: 'Callable[[dict[str, object]], None] | None' = None, *, overwrite: 'OverwritePolicy' = <OverwritePolicy.REFUSE: 'refuse'>) -> 'subprocess.CompletedProcess[str]'¶

run_with_progress(self, args: 'list[str]', show_percentage: 'bool' = True, *, overwrite: 'OverwritePolicy' = <OverwritePolicy.REFUSE: 'refuse'>) -> 'subprocess.CompletedProcess[str]'¶

FFprobeRunner¶

get_bitrate(self, input_file: 'str') -> 'int | None'¶

get_duration(self, input_file: 'str') -> 'float'¶

get_resolution(self, input_file: 'str') -> 'tuple | None'¶

get_version(self) -> 'str'¶

probe(self, input_file: 'str', *, raw: 'bool' = False) -> 'dict[str, Any]'¶

probe_media(self, input_file: 'str') -> 'MediaInfo'¶

probe_raw(self, input_file: 'str') -> 'dict[str, Any]'¶

JobCancelledError¶

JobExecutionError¶

JobResult¶

to_dict(self) -> 'dict[str, Any]'¶

JobStatus¶

JobTimeoutError¶

MediaInfo¶

to_dict(self) -> 'dict[str, Any]'¶

OverwritePolicy¶

PipelineCachePolicy¶

to_dict(self) -> 'dict[str, object]'¶

PipelineCompiler¶

compile(self, spec: 'PipelineSpec', *, variables: 'dict[str, str] | None' = None, force: 'bool' = False, timeout_seconds: 'float | None' = None, cache_enabled: 'bool | None' = None) -> 'PipelinePlan'¶

PipelineEvent¶

to_dict(self, secrets: 'tuple[str, ...]' = ()) -> 'dict[str, object]'¶

PipelinePlan¶

graph(self, format: 'str' = 'text') -> 'str'¶

to_dict(self) -> 'dict[str, object]'¶

PipelinePreflightEngine¶

prepare(self, pipeline: 'PipelinePlan', *, allow_existing_outputs: 'bool' = False) -> 'PreparedPipeline'¶

PipelineRun¶

to_dict(self) -> 'dict[str, object]'¶

PipelineRunner¶

run(self, pipeline: 'PipelinePlan', *, cancellation: 'threading.Event | None' = None, state_path: 'str | Path | None' = None, resume: 'bool' = False, receipt_dir: 'str | Path | None' = None, hash_content: 'bool' = False, event_callback: 'Any' = None) -> 'PipelineRun'¶

PipelineSpec¶

to_dict(self) -> 'dict[str, object]'¶

PipelineStepOutcome¶

to_dict(self, secrets: 'tuple[str, ...]' = ()) -> 'dict[str, object]'¶

PipelineStepPlan¶

PipelineStepSpec¶

to_dict(self) -> 'dict[str, object]'¶

Profile¶

to_dict(self) -> 'dict[str, Any]'¶

ProfileRegistry¶

get(self, name: 'str') -> 'Profile'¶

list(self) -> 'tuple[Profile, ...]'¶

load_file(self, path: 'str | Path') -> 'Profile'¶

plan(self, name: 'str', planner: 'WorkflowPlanner', input_file: 'str', output_file: 'str', *, subtitle_file: 'str | None' = None, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'¶

`BatchEvent`¶

`to_dict(self) -> 'dict[str, object]'`¶

`BatchItemOutcome`¶

`to_dict(self) -> 'dict[str, object]'`¶

`BatchJob`¶

`BatchManifest`¶

`to_dict(self) -> 'dict[str, object]'`¶

`BatchPolicy`¶

`to_dict(self) -> 'dict[str, object]'`¶

`BatchRun`¶

`to_dict(self) -> 'dict[str, object]'`¶

`BatchRunner`¶

`CapabilityUnavailableError`¶

`CapabilityInventory`¶

`missing(self, requirements: 'tuple[str, ...]') -> 'tuple[str, ...]'`¶

`supports(self, requirement: 'str') -> 'bool'`¶

`to_dict(self) -> 'dict[str, Any]'`¶

`CapturePolicy`¶

`CompressOptions`¶

`ConvertOptions`¶

`EnvironmentUnavailableError`¶

`ExecutionPlan`¶

`to_dict(self) -> 'dict[str, Any]'`¶

`ExecutionPolicy`¶

`ExecutionStep`¶

`FFmpegRunner`¶

`adjust_speed(self, input_file: 'str', output_file: 'str', speed_factor: 'float' = 1.0, audio_pitch: 'bool' = True, *, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

`execute_plan(self, plan: 'ExecutionPlan', *, cancellation: 'threading.Event | None' = None, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

`extract_thumbnail(self, input_file: 'str', output_file: 'str', timestamp: 'str' = '00:00:01', width: 'int' = 320, height: 'int | None' = None, quality: 'int' = 2, *, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

`generate_waveform(self, input_file: 'str', output_file: 'str', width: 'int' = 800, height: 'int' = 200, colors: 'str' = 'white', *, force: 'bool' = False, progress_callback: 'Callable[[ProgressEvent], None] | None' = None) -> 'JobResult'`¶

`get_version(self) -> 'str'`¶

`run(self, args: 'list[str]', progress_callback: 'Callable[[dict[str, object]], None] | None' = None, *, overwrite: 'OverwritePolicy' = <OverwritePolicy.REFUSE: 'refuse'>) -> 'subprocess.CompletedProcess[str]'`¶

`run_with_progress(self, args: 'list[str]', show_percentage: 'bool' = True, *, overwrite: 'OverwritePolicy' = <OverwritePolicy.REFUSE: 'refuse'>) -> 'subprocess.CompletedProcess[str]'`¶

`FFprobeRunner`¶

`get_bitrate(self, input_file: 'str') -> 'int | None'`¶

`get_duration(self, input_file: 'str') -> 'float'`¶

`get_resolution(self, input_file: 'str') -> 'tuple | None'`¶

`get_version(self) -> 'str'`¶

`probe(self, input_file: 'str', *, raw: 'bool' = False) -> 'dict[str, Any]'`¶

`probe_media(self, input_file: 'str') -> 'MediaInfo'`¶

`probe_raw(self, input_file: 'str') -> 'dict[str, Any]'`¶

`JobCancelledError`¶

`JobExecutionError`¶

`JobResult`¶

`to_dict(self) -> 'dict[str, Any]'`¶

`JobStatus`¶

`JobTimeoutError`¶

`MediaInfo`¶

`to_dict(self) -> 'dict[str, Any]'`¶

`OverwritePolicy`¶

`PipelineCachePolicy`¶

`to_dict(self) -> 'dict[str, object]'`¶

`PipelineCompiler`¶

`compile(self, spec: 'PipelineSpec', *, variables: 'dict[str, str] | None' = None, force: 'bool' = False, timeout_seconds: 'float | None' = None, cache_enabled: 'bool | None' = None) -> 'PipelinePlan'`¶

`PipelineEvent`¶

`to_dict(self, secrets: 'tuple[str, ...]' = ()) -> 'dict[str, object]'`¶

`PipelinePlan`¶

`graph(self, format: 'str' = 'text') -> 'str'`¶

`to_dict(self) -> 'dict[str, object]'`¶

`PipelinePreflightEngine`¶

`prepare(self, pipeline: 'PipelinePlan', *, allow_existing_outputs: 'bool' = False) -> 'PreparedPipeline'`¶

`PipelineRun`¶

`to_dict(self) -> 'dict[str, object]'`¶

`PipelineRunner`¶

`run(self, pipeline: 'PipelinePlan', *, cancellation: 'threading.Event | None' = None, state_path: 'str | Path | None' = None, resume: 'bool' = False, receipt_dir: 'str | Path | None' = None, hash_content: 'bool' = False, event_callback: 'Any' = None) -> 'PipelineRun'`¶

`PipelineSpec`¶

`to_dict(self) -> 'dict[str, object]'`¶

`PipelineStepOutcome`¶

`to_dict(self, secrets: 'tuple[str, ...]' = ()) -> 'dict[str, object]'`¶

`PipelineStepPlan`¶

`PipelineStepSpec`¶

`to_dict(self) -> 'dict[str, object]'`¶

`Profile`¶

`to_dict(self) -> 'dict[str, Any]'`¶

`ProfileRegistry`¶

`get(self, name: 'str') -> 'Profile'`¶

`list(self) -> 'tuple[Profile, ...]'`¶

`load_file(self, path: 'str | Path') -> 'Profile'`¶

`plan(self, name: 'str', planner: 'WorkflowPlanner', input_file: 'str', output_file: 'str', *, subtitle_file: 'str | None' = None, force: 'bool' = False, timeout_seconds: 'float | None' = None) -> 'ExecutionPlan'`¶

`PreparedPipeline`¶